Tag: growth

Marco Antonielli ’12 (International Trade, Finance, and Development) is a consultant with Nathan Associates in London. Prior to this he was a consultant at the OECD in Paris and a research assistant at the Bruegel think tank in Brussels. The following piece by Marco originally appeared on Nathan’s website. (All opinion and analysis are only those of the author.)

In a global economy with fewer opportunities to industrialize, low-income countries will need to embed the service sector in their vision for inclusive growth.

Amid a gloomy global economic outlook and crashing commodity prices, low-income countries ended 2015 with the slowest growth since 2009, and remain in serious need of new sources of inclusive growth. One major challenge to achieving higher living standards stems from the vast income and productivity gaps within these countries and in relation to the rest of the world.

Large-scale industrialization has traditionally been viewed as the main solution for bridging these gaps, as well as a strategic objective to create jobs and support future growth. Yet latecomers to development may have embarked on a path on which manufacturing—arguably the most promising sector—is expanding slowly in absolute terms, and often shrinking in relation to GDP. The questions are then: why do low-income countries struggle to industrialize? And could alternative sectors such as services replace manufacturing as engines of inclusive growth?

Growing out of the Traditional Economy

Let’s take a step back. While all economies are characterized by varying degrees of productivity and dynamism among sectors and businesses, the low-income countries feature tremendous structural gaps within their economies. Most of the workforce is employed in informal and traditional agricultural businesses, while manufacturing is limited and not fully organized and the dynamic services are largely confined to the cities. Also the modern and formal agricultural businesses are not as widespread as they could be.

To escape poverty, millions of workers need to move from low-productivity sectors and businesses, mainly agriculture, to high-productivity ones, where they will find better and more secure jobs. The reallocation of resources to modern and dynamic sectors can generate positive transformation and help low-income countries achieve inclusive growth.

However, economic transformation can lead to labor and capital being reallocated to more inefficient activities. Recent studies have found that from a macroeconomic perspective, structural transformation (i.e., intersectoral movement of resources) can be a drag on growth for long periods of time, and this is part of the reason why the growth dynamics of low- and middle-income countries have been so diverse. Such a pattern is illustrated in figure 1. Observing the breakdown (“decomposition”) of aggregate productivity growth in the sum of sectoral components and a component accounting for cross-sectoral labor reallocation, it can be noted that between the 1990s and the 2010s Asian and Eastern European countries benefited from the structural transformation of their economies, while Latin American and Sub-Saharan African countries had the opposite experience. Developing countries are therefore not necessarily transforming well over their growth paths.

Organized and modern manufacturing is commonly understood as the business where workers in informal or more traditional forms of agriculture should be reemployed. This is because, while manufacturing is not necessarily the most efficient sector in the economy, it can be a growth accelerator and engine of inclusive growth for at least three reasons. First, manufacturers in emerging economies can benefit from manufacturing technologies developed in more advanced countries, and can achieve fast productivity growth. Second, manufacturing can absorb unskilled labor—thus providing improved employment opportunities for agricultural workers in low-income countries. Finally, manufacturers can export their products, so their growth will not be confined by limited domestic demand. Tradability is key, because high productivity growth can quickly lead producers to lower their prices and shed labor and capital if they cannot scale up their sales in bigger markets.

Is Industrialization a Broken Engine?

Virtually all successful emerging economies in the past 30 years have industrialized by leveraging this potential. Manufacturing offers opportunities to diversify away from agricultural and other traditional products, and helps the country pull itself out of poverty. But is this growth trajectory still feasible for today’s developing countries?

In most countries, the share of jobs and GDP arising from manufacturing expands in the early stages of development, then peaks and starts shrinking as relative prices decline and the economy matures. As Dani Rodrik and others have recently argued, latecomers to development in Africa and Latin America are hitting the peak earlier in the process, and are starting to deindustrialize when manufacturing has exploited only part of its potential. Ghani and O’Connell, for example, explore this inverted-U relationship between the level of economic development and the industry’s share of total employment, in a panel of 100 countries. They show how, in recent times, jobs in industry have grown more slowly and shrunk earlier in the development process (figure 2). The engine of industrialization seems to be running out of steam.

According to Rodrik, this manufacturing decline is mainly due to the adverse effects of trade and globalization on low- and middle-income countries in Africa and Latin America in two respects. First, these countries struggle in the international goods market because of a decline in the relative price of manufacturing in advanced economies, where technological progress has pushed up efficiency and reduced the need for expensive labor. Second, low transport costs and low trade barriers expose them to hyper-cheap production from East Asia, effectively reducing the scope for “import substitution” to expand the boost in manufacturing exports to the wider economy. This would suggest that today’s low-income countries will need to wait until East Asia becomes expensive before they industrialize.

A competing theory is that the low-income countries have subscribed to a trade system that is altogether unfavorable to them. On the one hand, to get access to international markets they are required to forgo protectionist policies that foster import substitution and screen nascent industries from foreign competition during their early development (see e.g., Ha-Joon Chang). On the other hand, trade barriers to advanced markets like the EU are set low for raw materials such as coffee beans and cocoa pods but high for the products obtained from processing of materials—in these examples, roasted coffee and chocolate. This means that the entry points to industrialization of commodity-dependent countries are essentially shut down.

Help Services

Both theories offer plausible explanations of why low-income countries struggle to industrialize. While more evidence on the causes of the problem is needed, it is increasingly clear that vast-scale industrialization has not featured in the development of most low-income countries. In contrast, the service sector has grown rapidly and absorbed lots of labor. Looking at Sub-Saharan Africa, for example, in the 15 years of this century . This pattern does not adequately represent how low-income countries grow and expand their productive capabilities, at least in that it does not capture the role of the variety and complexity of the products menu offered by these countries. Yet it can raise the question of how services can replace manufacturing as an engine of inclusive development. At least three routes can be identified.

First, there is a fringe of dynamic and tradable services that can boost the economy just as manufacturing does. Banking, customer services, and communications are examples of services which the ICT revolution has opened up to trade, and which can take low-income countries on a growth escalator, as the Indian boom has demonstrated. Crucially, investments in infrastructure, education, and human capital need to be made to facilitate development in these services. An alternative service attracting foreign demand with decent labor-absorption capacity is tourism.

Second, services are crucial inputs to manufacturing and there is evidence that their importance is growing. Hence cheap and efficient services such as transport and telecommunications can translate into stronger competitiveness of the tradable sector—both manufacturing and services.

Finally, the fact that manufacturing and services are becoming increasingly “blurred,” with services activities making up a higher share of manufacturing output, means that low-income countries could exploit a competitive edge on relevant service tasks. Moreover, these tasks can often be unbundled from merchandise production and traded along the global value chain. Logistics, marketing and post-sales services have been on the rise, not only in developed economies but also in developing ones. Furthermore, this trend could lead to a misinterpretation of statistics based on obsolete sector categories, effectively misleading our understanding of structural change.

In sum, the service sector offers new and interesting opportunities for growth, both through tradable services that plug directly into the global economy and through services that support competitiveness of manufacturing. In a global economy with fewer opportunities to industrialize, low-income countries will need to embed the service sector in their vision of inclusive growth and focus on the conditions that enable these opportunities.

Evan Seyfried ’16 shares the following summary of a talk given by Princeton’s Atif Mian this May to the UPF Department of Economics and Business. Follow Evan on Twitter @evanseyf

The bubble

In 2006, house prices in the U.S. reached their all-time peak. The S&P/Case-Shiller Housing Price Index had doubled in just eight years (not accounting for inflation).1 The year before, Robert Shiller (whose work on historical housing prices led to the creation of the Case-Shiller Index) had published an update to his book Irrational Exuberance warning that recent growth in housing prices was historically unprecedented—he argued that houses were wildly overpriced and would likely revert back to a relatively constant historical value in the long run.2 His research showed that if you looked at real prices (inflation-adjusted) in the U.S. housing market prior to the early 2000s bubble, you would find that prices have not changed much since 1890!

Figure 1. Case-Shiller Home Price Index from 1890-2014. Values are real (corrected for inflation) and are set relative to 1890 prices (which is defined as 100). Source: Data from Robert Shiller, graph from The Atlantic3

The frenzy of the early 2000s finally caught up with lenders, homeowners, and investors, who began to doubt the continued rise of house prices. In late 2005, with interest rates rising, a growing number of homeowners with Adjustable-Rate Mortgages (ARM) began to default on their mortgages. Finally, by the end of 2006 the housing bubble began to collapse under its own weight, and the shockwaves ripped through the financial sector—which had bet heavily on the U.S. housing market through mortgage-backed securities and newer exotic financial instruments. French bank BNP Paribas, on August 7, 2007, famously suspended withdrawals from its investment funds associated with subprime mortgages, a move that triggered a shadow banking run, and is often considered the official start of the financial crisis—when the housing market instability truly began to upend the financial sector. What followed was the most severe financial crisis since the Great Depression and a long recession for the rest of the U.S. economy.

But there is still much to be learned about the interaction of the housing bust (leaving many homeowners with very high debt compared to their assets), the crisis in the financial sector (wherein banks have been generally unwilling to either extend new credit or restructure existing loans), and the continuing economic malaise in the U.S. and other economies around the world.

From the housing bubble to household debt

A great deal of Princeton economist Atif Mian’s research—much of it in collaboration with University of Chicago economist Amir Sufi—has studied these interactions, exploring the fallout from the housing bubble in the U.S. and the subsequent “debt overhang.”

What is household debt overhang?

Imagine a family owes $200,000 on their mortgage. If the market crashes and the house value suddenly declines to $180,000, then the family now owes $20,000 more than the value of their house. Thus, even if the family chooses to sell the house, they will not be able to pay back the mortgage in full. This is also called being “underwater” on a mortgage. In the context of all household finances, debt overhang is a similar concept to being underwater, and refers to the amount of indebtedness of a family beyond the value of their assets, taking into account their anticipated income. Debt overhang makes a household unattractive to lenders (both for new loans and for refinancing old loans), because they do not have any collateral that is not already used to cover existing debt.

Note that household debt is treated separately from other private sector debt (mainly non-financial firm debt), and shows notably different dynamics. All of Atif Mian’s research mentioned here focuses specifically on household debt.

In 2013, Mian published evidence that poorer families who were highly leveraged in the housing market reacted very sharply to the loss of wealth when their homes depreciated following the housing bust. Because their marginal propensity to consume out of housing wealth (how much families spend knowing that they have a certain amount of wealth in their house to fall back on) is higher than for middle- or upper-income families, their consumption dropped disproportionately in the years after the bubble.4 Of course, at the individual level this behavior is rational, but at the national level low consumption growth in a demand-constrained economy has created a negative feedback loop of lower job growth, lower income growth, and a further drop in consumption growth.

One of the takeaways from this body of research is that governments and international finance organizations need to do a better job of properly accounting for how private sector debt affects consumption. Optimistic forecasts for recovery from the 2008-2010 Great Recession did not sufficiently account for depressed demand as homeowners and those with credit card and student debt eschewed consumption to deleverage themselves. In a comment on Karen Dynan’s research on household debt overhang and consumption, Mian wrote: “… macroeconomic policy in a world where consumption is driven by debt overhang needs to be seen through its implications for the net worth of the borrowing households.”5

Imperfect instruments?

But Mian also wanted to take these insights from the Great Recession and ask more fundamental questions about private debt and predictions of economic growth: Was consumption affected similarly affected during other periods of high household debt? Do we see similar household debt effects in other countries? If so, how does this extra drag on consumption affect how economists forecast economic growth?

Atif Mian. Photo: The New York Times

Mian recently gave a lecture at the Universitat Pompeu Fabra in Barcelona, presenting the findings from his attempt to answer those questions. (The working paper, coauthored with Amir Sufi and Emil Verner, is available from the National Bureau of Economic Research.6 ) They took a sample of 30 countries (mostly advanced economies) and compiled private debt data back to 1960. Then they identified shocks to household credit and looked at the relationship between those shocks and subsequent GDP growth. (In this context, shocks should be thought of as sudden increases in the availability of credit.)

Initially they found that high growth in household credit was predictive of subsequent low GDP growth. But they needed to identify the nature of those credit shocks to find possible causal channels. According to Mian they wanted to “rule out demand-driven shocks.” Demand-driven shocks come from the consumer side and could be an increase in the use of credit to smooth lifetime consumption, or as an “insurance effect” to get liquidity today due to uncertainty or an expectation of economic shocks tomorrow. On the other hand, a supply-driven credit shock would be banks extending more and more credit due to government policy changes or financial innovation.

The first demand-driven possibility is relatively simple to disprove. Because the Permanent Income Hypothesis suggests that households borrow today in the expectation of higher future income, the fact that household debt increases should be indicative of economic growth. As mentioned before, Mian, Sufi, and Verner find the exact opposite relationship. The second demand-driven possibility is unlikely because much of the growth in household debt across all the countries in the survey is in mortgage debt, which is generally not taken on to provide liquidity.

Next, they looked into the supply-driven credit shock mechanism and tried to find a way to overcome the presumably endogenous relationship between credit supply shocks and subsequent lower GDP growth. The mechanism must explain why people borrow in the first place, especially what causes them to over-borrow (what Mian calls an “aggregate demand externality”—an effect that spills over to other borrowers), and explain why excessive borrowing actually leads to a decline in real output (what Mian calls “macro frictions” that generate the slowdown, such as monetary policy and “wage rigidity”). As the authors write in the paper: “The key ingredient in this model is an aggregate demand externality that is not properly internalized by borrowing households at the time they make their borrowing decision.”

Two problems remained. First, the authors had to come up with a measure of “credit supply shocks” that could apply to dozens of different countries. Second, they had to choose a measure that could help identify the causal relationship, not just the correlation. Their solution was to use one measure for the U.S. (share of debt issuance by risky firms) and a simpler one for non-U.S. economies (the spread of sovereign debt yields compared to equivalent U.S. Treasury notes). According to Mian, these are “not instruments in the usual sense of the word” (which must satisfy the requirements of independence from the outcome variable and relevance to the explanatory variable). Rather, they are “imperfect instruments” (see Nevo and Rosen, 2012.7 for more information) and, per Mian, “as long as we can sign the covariance of the instrument, we can partially identify the range in which the coefficient lies.” In other words, because these proxies for credit supply shocks typically signify expectations of good times, then if we see that they actually predict bad times, we can at least identify a range of values for how strong the link is between an increase in household debt and subsequent low growth.

The methodology is admittedly complex, and audience members had some reservations about how the authors had dealt with household debt (particularly since household debt is mostly mortgage debt). One audience member suggested that housing bubbles could be the main driver of subsequent low growth, with the extension of credit simply a side effect. Mian acknowledged that he cannot outright reject this concern, but added that the results are robust to controls for house prices, so the bubbles should be controlled for. Another audience member suggested that this could be tested for if the data set included any countries which had seen a credit boom with no attendant housing bubble. There are, in fact, some countries in the data set, but, as Mian stressed, there was not enough of a subsample for a strong statistical test of this hypothesis.

Onward to global growth!

After presenting the “within country” results—showing that household credit supply shocks tended to lead to lower growth in the five or so years following—Mian pivoted to the global portion of the paper. The goal here was to establish the spillover effects of these credit supply shocks among different countries. Sure enough, Mian stated that “the global cycle is more destructive” due to financial spillovers between countries. Because the growth slowdown in a given country after the credit shock leads to a reduction in imports, the problem is transferred to that country’s trading partners. Furthermore, the effects are exacerbated by “macro frictions,” especially in countries that employ fixed exchange rate regimes, borrow primarily in foreign currency, and are near the zero interest rate lower bound (although recently the zero interest rate bound has been proving not to be much of a hard bound after all). Figure 2 shows these global aggregate effects.

Mian stressed that these dynamics between debt and growth, especially the global ones, should be seen as relatively recent (“last-forty-years effects”) side effects of globalization and the financialization of household debt. He concluded that governments must respond to these powerful forces with targeted macroprudential policies, and forecasters at organizations like the IMF and OECD must learn to better account for household debt in their growth projections.

Lecture summary by Tuomas Kari ’16 (Master’s in International Trade, Finance, and Development)

The former Chief Economist of the World Bank and member of Barcelona GSE Scientific Council Justin Yifu Lin visited Barcelona GSE on May 2nd to give a special talk to the Master students on a new approach to development policy, titled “New Structural Economics: The Third Wave of Development Thinking”. Professor Lin, who currently teaches at the National School of Development at the University of Beijing, outlined the history of development economics and its shortcomings. The goal of the lecture was to derive lessons for optimal policy and then expand upon the idea of new structural economics, the approach Prof. Lin himself advocates.

Structuralism and neoliberalism

Prof. Lin divided the history of development into two time periods: structuralism that was dominant from 1950 to the 1980s, and neoliberalism that has been the main viewpoint up to this day. Structuralism tended to assume that there were market failures that needed to be corrected with industrial policy, such as import substitution. The failure of these policies is well documented as the government-subsidized industries rarely survived at global markets and distorted the countries’ economies. Neoliberalist reaction emphasized deregulation to rid the economy of rent seeking and liberalization to let markets determine the allocation of resources. But this too failed in developing countries to reach steady growth. Often, liberalization led to the collapse of entire sectors, high unemployment and subsequent political unrest.

The main exception to these consensus policies throughout the last half a century have been the East Asian Tigers, Hong Kong, Singapore, South Korea and Taiwan, countries that followed a dual track of capitalist and state-directed policies and achieved unmatched growth rates. As these countries were initially too poor to afford expensive subsidies to heavy industry, they promoted production lower in the value chain, and even then only by piece-meal measures. According to Prof. Lin, this lack of better options guided the Tigers to good policies by accident.

Professor Lin delivered the Barcelona GSE Lecture at Banc Sabadell later the same day to the entire BGSE community.

Economic growth as a result of structural transformation

New structural economics is an attempt to study the determinants of economic structure and its evolution using neoclassical methods. Prof. Lin starts from the hypothesis that economic structure is endogenous to the country’s endowments and optimal policy guides the economy to activities where it enjoys comparative advantage. If a country attempts to transform its economy to activities other than those that utilize its endowments, this will only result in distortions, breaking down of market mechanisms and rent seeking. Optimal policy must start from the development of endowments (capital stock, human capital etc.) and only after try to deal with the production structure. As economic growth is ultimately a result of structural transformation, Prof. Lin argued that governments must engage in first building up the necessary endowments and then using industrial policy to help firms enter into business.

The preconditions for economic growth are having a functioning market economy efficiently allocate resources across sectors and firms, and a facilitating state that provides transitional support for firms entering and exiting the market and liberalizing the economy gradually using discretion. Lin claimed would lead to competitiveness, openness to trade, and strong fiscal and external accounts, which allow the economy to avoid crises and engage in countercyclical policies. Another benefit would be high returns to investment that provide incentives to save.

Room for more economic research

Prof. Lin promoted the setting up of Special Economic Zones to allow firms to do business free from distortions and also work as laboratories for the government to see what the comparative advantages of the economy are. He ended the lecture by proposing the development of theoretical models capable of explaining these dynamics as a fruitful avenue for the future economists in the audience.

Lecture summary by Evan Seyfried ’16 (Master’s in Economics of Public Policy). Above, the author talks with Robert Lucas after the lecture.

The modish Banco Sabadell Lecture Hall, overlooking grand, prosperous Avinguda Diagonal, is filled to capacity this Thursday evening. Nobel laureate economist Robert Lucas is here to present the 34th Barcelona GSE Lecture, and the GSE community is eagerly anticipating the talk.

“What was the Industrial Revolution?”

The topic would have seemed almost trite in less-skilled hands. Lucas, however, over the past decade has focused his talents on exploring economic models that might explain rapid industrialization like that of the United Kingdom starting in the late 18th century. He views the rise of urbanization and industrialization through the lens of economist Gary Becker’s theory of population fertility and couples it with a human capital growth model.

This talk draws heavily from Lucas’s recent research on human capital and economic growth1, the diffusion of the Industrial Revolution2, and a rejection of the “great men” hypothesis of economic progress3.

The central hypothesis of his lecture tonight is, essentially, that of his 2015 paper on economic growth, with its blissfully short abstract:

“This paper describes a growth model with the property that human capital accumulation can account for all observed growth. The model is shown to be consistent with evidence on individual productivities as measured by census earnings data. The central hypothesis is that we learn more when we interact with more productive people.”1

From this basis, Professor Lucas presents his most recent work on the topic. He begins with a graph—how else would an economist begin any lecture?—showing the striking relationship between a country’s prosperity (measured in GDP per capita) and the share of its population employed in agriculture.

Why is the relationship between these two variables so consistent? Later in the lecture, Lucas will develop his model based on a “dual economy” of low-skilled agricultural workers and various levels of skilled urban dwellers.

But first, a little history.

“Macroeconomics’ finest hour.” (A brief historical digression.)

Thomas Robert Malthus, English cleric and scholar, became famous (and, to some, infamous) when he published “An Essay on the Principle of Population” in 1798. The essay neatly distilled a framework for pre-industrial population dynamics:

“Yet in all societies, even those that are most vicious, the tendency to a virtuous attachment is so strong that there is a constant effort towards an increase of population. This constant effort as constantly tends to subject the lower classes of the society to distress and to prevent any great permanent amelioration of their condition.”4

Its publication led to a massive controversy that rapidly spread across the landscape of political economy. Although Malthus’s work was not nearly as apocalyptic as his deriders asserted, it still pointed out uncomfortable truths about the seemingly unrelenting misery of the lower classes, even in “advancing” nations.

A century and a half later, economist Gary Becker took up the Malthusian mantle with his seminal work, “An Economic Analysis of Fertility,” a study of the dynamics of family planning and income. Becker explicitly acknowledged his debt to Malthus: “[…] Malthus’ famous discussion was built upon a strongly economic framework; mine can be viewed as a generalization and development of his.”5 Becker’s further research concluded that viewing fertility as a result of marginal-cost/marginal-benefit decisions is a satisfying way to explain the phenomenon of high-income families voluntarily lowering their fertility rates. His framework implies that families with more human capital invest more resources in fewer children.

Professor Lucas calls the Malthusian insight and the subsequent robust debate among political economists of the day “macroeconomics’ finest hour.”

The Path Off the Farm: What Is an Industrial Revolution?

Lucas now presents his synthesis: Becker’s fertility model combined with Lucas’s own human capital model, both placed in the context of the urban-agricultural dual economy.

Like Becker, Lucas’s model has parents view their children as “durable goods” that yield a “psychic utility” but also impose costs. As families move up the socioeconomic ladder, they make different decisions regarding investment in the “quality” of the children (everything from time spent teaching, to money invested in tutors and private schools). Over time, the quantity/quality balance leads to lowering fertility among higher socioeconomic classes.

In the dual-economy framework, rural (landless or small proprietor) farmers are pushed by wage considerations to move into dynamic urban environments as low-skilled workers. At first, with no wealth to invest in their children, they make “quantity” a priority over “quality.” Over generations, however, there is a tipping point where a given family has accumulated enough resources to make meaningful human-capital investments in their children. Once this occurs, they can now move up to the higher-skilled tiers of society. Crucially, it is this accumulation, not of wealth, but of human capital, that drives further growth in Lucas’s model. The speed at which these changes occur depends on the magnitude of “interactions” in society: how often and to what degree people engage with one another in productive exchanges—anything from academic discussions to business deals.

A key mechanism in the model is that economic growth itself is what allows the low-skilled workers, coming from the farms, to dependably get better and better jobs over time. Thus, the dynamic is self-reinforcing as more rural workers move to the cities.

When considering the Industrial Revolution, we can appreciate how natural it would be to dismiss the intangible, fuzzy concept of “human capital” and only focus on material capital: factories, infrastructure, mines, etc. But if we view the Industrial Revolution with Lucas’s model in mind, we can at the very least see that Lucas’s statement from his 2015 paper—”human capital accumulation can account for all observed growth”1—is quite plausible.

Later in the same paper, Lucas asserts: “The contribution of human capital accumulation to economic growth deserves a production function of its own.” 1 In the model Lucas has presented tonight, he answers his own demand. There is, indeed, a “production function” for human capital, and when it is coupled to a fertility model, it can show the dynamics of rapid urbanization and economic growth. In other words, it can model an industrial revolution.

To use Lucas’s own words from the lecture: “We used to think of the Industrial Revolution as factories and coal, but I think the main consequence was the emergence of the bourgeoisie who are just creating things out of nothing, generating wealth and production.”

Postscript

What does this all mean? What are the implications of this model in 2016?

We go back to the graph showing the relation between GDP per capita and share of population in agricultural work. Lucas mentions how many areas of the world are still in the upper left portion of the graph—poor, agricultural, unskilled-labor-intensive economies. According to Lucas, we must not be deluded into thinking that a pastoral lifestyle is something to be preserved at the cost of indefinite poverty. Lucas states, “The idea that you can prettify this lifestyle is just plain wrong.” Rather, we have a collective interest in the flourishing of all people around the world, and we have emerging evidence that investment in human capital, coupled with smart urbanization, is one of the best ways to achieve it.

The questions following the lecture are—as expected from economists—pointed. In response to questions about the refugee and economic migrant crisis in the EU, Lucas denies that his model says anything specific about it, but states emphatically that he supports immigration in general. Finally, when asked about the prospects of continued economic growth, given recent anxiety about economic stagnation, Lucas responds that since the Industrial Revolution we have seen stable growth unlike any period before in recorded history. He believes that growth will continue, as capitalism reinvents itself yet again, this time for the information age—though he admits that “flush toilets are way more important than Facebook.”

With that, the lecture concludes, and the lucky attendees weigh the expected utility of waiting in line to speak with the most influential living economist against the expected utility of beating the rush to the cava and jamón ibérico at the reception. The gears of the market keep turning.

This empirical exercise examines how export diversification is related with higher GDP per capita growth.

Post by Facundo Abraham ’16 and Alberto González de Aledo Pérez ’16, current master’s students in the Barcelona GSE International Trade, Finance, and Development Program.

The diversification of exports exemplifies the transition of economies towards higher levels of development with more complex economic structures. It can also facilitate risk reallocation and mitigate negative terms of trade shocks in a certain industry or geographical area. In addition, countries exposed to international competition can benefit from better ways of doing business.

This empirical exercise examines how export diversification is related with higher GDP per capita growth. For the most part it follows the dynamic panel data model proposed in Hesse (2008) for a sample of seven Asian emerging markets and developing economies. The author illustrates that these countries are considered to be a cluster characterised by both high degrees of export diversification and GDP per capita growth in the long run. The exercise updates the calculations made for this sample.

Model specification and data

The augmented version of the Solow growth model provides the necessary framework.

The dependent variable denotes the natural log difference of GDP per capita adjusted for PPP, retrieved from the World Bank. The independent variables are the initial income and a vector of growth determinants. Gamma captures the time-invariant unit-specific effects and eta the time effects.

The vector of growth determinants consists of human capital, the natural log difference of population, the share of investment in total GDP and a measure of export diversification. Population and investment are taken as proxies for employment and savings, respectively. Together with human capital, these were retrieved from the Penn World Table 8.1 release.

Export diversification is defined as the residual of a normalised Herfindahl-Hirschman index.

The equation exhibits reporter country i exports commodity x to partner j. The data was retrieved from the UN Comtrade database. To compute the indices, the chosen breakdown was the ninety-seven chapter disaggregation†.

The sample period used as an input to the model runs from 1996 to 2011 on an annual frequency and covers Bangladesh, China, India, Indonesia, Malaysia, the Philippines and Thailand.

The model is estimated as a system generalised method of moments (GMM) similar to Arellano and Bover (1995) and Blundell and Bond (1998). This specification uses as instruments the first-differenced equations with up to four lag levels and equations in levels with up to four lag first-differences.

Estimation and robustness check

Column 1 in Table 1 presents the estimation for the augmented Solow model. The computed coefficients are significant and have the expected sign. There is evidence from column 2 that export diversification has a positive and significant effect on GDP per capita growth as has already been predicted in previous studies. Columns 5 to 8 supports the robustness of export diversification with the inclusion of different control variables. If openness is entered as it is in column 8, initial income becomes not significant. The performance on this indicator varies across countries in the sample. In the case of the Philippines and Malaysia there is a downward trend. However, in the former the initial values were remarkably high. China has also experienced a decrease in its level of openness in the aftermath of the crisis.

Export diversification is not a linear process. It is better depicted as an inverted U-shaped pattern. On the one side, early stages of development are characterised by a concentration in production of a handful of items or extraction of natural resources. On the other side, advanced economies also specialise their exports in a number of items. The development of complex economic structures is a harbinger of increasing competitiveness and export diversification in emerging and developing economies.

Columns 3 and 4 test for the presence of nonlinearity in the relation between export diversification and GDP per capita growth. The squared term of export diversification has a negative effect on GDP per capita growth. However, it is not significant in this specification. On the contrary, the interaction term is significant and changes sign. These regressions show some evidence of a certain degree of nonlinearity.

Concluding remarks

The exercise has examined the link between export diversification and GDP per capita growth in a cluster of economies that have a particular intense relation among these indicators. The results illustrate that income could have benefited from the diversification of exports. These findings are robust and are consistent to the sample used in Hesse (2008) and previous literature on the topic.

Future research could include further variables such as partner diversification or trade in services statistics. However, the former is limited compared to trade in commodities. In addition, in order to evaluate shocks in price and cost competitiveness, real effective exchange rates could be introduced.

Roodman, D. (2009). “How to do xtabond2: An Introduction to Difference and System GMM in Stata”. The Stata Journal, Vol. 9, No. 1, pp. 86-136.

† Trade data is reported in the Harmonised System international standardised nomenclature for traded commodities. This convention organises items into twenty-one sections, ninety-seven chapters and subsequent headings and subheadings. For example, section 15 breaks into 12 chapters such as iron and steel (72) and articles thereof (73).

About the authors

Facundo is a current student at the International Trade, Finance and Development program. Previously he worked in consulting projects on financial regulation and supervision in Latin America. He graduated in Economics from Universidad Torcuato di Tella. Connect with Facundo on Linkedin.

Alberto is a current student at the International Trade, Finance and Development program. He is a former Economist in BBVA’s Economic Research Department. He holds a BSc in Economics from Universidad Carlos III de Madrid. Connect with Alberto on Linkedin or follow him on Twitter.

The energy industry in Mexico is experiencing the biggest paradigm shift in the past seven decades, since the oil expropriation in the late 30’s. The energy reform that was recently enacted will dramatically change the way the energy sector is developed in Mexico, meaning the most significant economic happening since the execution of NAFTA, in 1994. Said reform will shake the Mexican energy industry vigorously, transforming a monopolistic sector operated by two state companies that performs the vast majority of the productive sector activities, into an open-market industry where players can freely participate through clear and transparent rules, under the regulation of operators and agencies endowed with broad powers. The profound changes brought by the reform occurred both in the substantive areas of the industry and in the institutional structures that shape the energy sector. In one hand, the new legal framework redefined the way the activities that constitute the productive chains of the hydrocarbons and electricity sectors are carried out; in the other hand, the institutions responsible for supervising and regulating the market performance were considerably strengthened.

Naturally, as a new market emerges, market problems also emerge. Therefore, it will be essential that the new Mexican energy market is wrapped by rules and institutions that seek to correct eventual market failures that arise, and that through their actions, establish an appropriate competitive process that yields benefits to competitors, to final consumers, and of course, to the Mexican State.

Oil&Gas

Modifications made to the Mexican Oil&Gas sector meant undoubtedly, the most important change in the whole energy industry, as a result of the energy reform. Said sector becomes an open market, where Petroleos Mexicanos (Pemex) –formerly the State-owned company that carried out all Oil&Gas exploration and exploration (E&E) activities, will compete against other players from the private sector. This competitive process is implemented through tenders conducted by the federal government, where both the private sector and Pemex will freely participate, in order to be granted with contracts for substantive E&E activities. Transparency will be an element of the utmost importance during the bidding rounds, since it will secure that Pemex and the private sector compete on equal grounds; in other words, a fair and clean competition process will only be possible as long as the federal government does not favor Pemex –which despite its participation in the open market, will remain as a state owned company- or any other bidder in the development and further resolution of the aforementioned bidding rounds, or allow any anti-competitive practices to take place (such as collusive behaviors among the bidders).

A fair and clean competition process will only be possible as long as the federal government does not favor Pemex / Flickr / CC

As for midstream activities, the energy reform introduced a new market dynamic that will foster a more effective and fair competition process. Currently, the activities of transport, storage and distribution that are developed through the pipeline grid will be operated and managed by a new government agency, the National Center for Control of Natural Gas (CENAGAS). This entity will assume control and ownership of all pipeline infrastructure that today belongs to Pemex[1] – which, due to its economic features, constitutes a natural monopoly-, and administer the activities carried out there. The CENAGAS will operate as a figure internationally known as an “ISO” (independent system operator), and will be obliged to fulfill important mandates, such as granting open and non-discriminatory access to the grid to all participants (including Pemex) and avoid problems of vertical integration in regulated activities, among others.

Electricity

The electricity sector in Mexico will also be transformed significantly by means of the energy reform, since it will stop being a vertically integrated industry where a State-owned company (Federal Electricity Commission “CFE”) conducts all activities of the productive chain industry, in order to be transformed into a liberalized sector where undertakings (both public and private) will compete against each other in an open market, aiming to satisfy the needs of consumers.

For such purpose, a wholesale spot market will be put into place. Said spot market will seek to replicate international models in order to foster competition among different companies that will be able to generate, trade and supply energy to final users. Domestic supply will be carried out by CFE –at a regulated tariff-, acquiring energy through tender processes, while industrial supply will happen through a free competition process, where generators, suppliers and consumers will complete transactions at market, non-regulated prices. In order to regulate the new market structure, the Government created the National Center of Energy Control (CENACE), which will serve as an ISO, aiming to operate and control the electric grid.

CENACE will be in charge of different relevant tasks, such as the granting of open access to undertakings participating in the electric industry, controlling the allocation of power into the grid (both demand and supply), surveilling the continuous bids posed by market participants into the spot market (in order to avoid coordinated anti-competitive effects) and coordinating the transactions executed by the market players, as well as the configuration of the market, in terms of possible vertical integration in the performance of activities by companies. This market will be particularly interesting in terms of competition policy, since CENACE will be in charge of regulating the operation of a natural monopoly –the electric grid- which is owned by one of the participants of the market, the CFE, which will compete against other undertaking in the activities of generation and supply of power; this represents a very unique case in the world, and will be added as one of the main challenges that Mexican authorities will face with the implementation of the energy reform.

Regulators and entities of the energy sector

One of the great challenges of the reform is to establish an institutional framework capable of operating the new emerging energy markets in Mexico, in which various companies (public and private) will interact in a competitive environment, hitherto unknown for the country. Of course, in order to accomplish this goal, it is imperative to create strong institutions, with high degrees of independence, able to issue clear regulations and impose heavy penalties to regulated undertakings.

Both regulatory agencies[1] and ISO’s will need to follow closely the development of the energy markets, and make sure that competition is achieved. Unlike what happened with the IFETEL, which is the independent body responsible for regulating the telecommunications market in Mexico, regulators and ISO’s in the energy sector were not endowed with broad powers in competition policy matters. In this sense, and despite some of its powers seek to create conditions of competition, these institutions will have to interact closely with the Federal Competition Commission, in order to timely detect and punish anti-competitive practices in the industry, in order to correct market failures and increase consumer welfare.

[1] Regulatory Commission of Energy and National Hydrocarbons Commission

Conclusions

Energy reform emerges as a great opportunity for Mexico to join the global trailblazers in the sector. At first glance, the work has been done satisfactorily, as sufficient legal and institutional conditions for implementing competitive markets were generated, where agents will interact correctly, generating consumer welfare. However, the correct development of the industry will depend not just on the rules and the institutions itself, but on the right behavior of both authorities and undertakings. Possibly the only advantage that Mexico has to be the second-to-last country in the world to undertake an opening process of this nature, is that it had the opportunity to study similar processes, and learn from positive and negative experiences in other countries. Now the challenge is to test that knowledge, and build a successful energy sector that can boost growth in the country.

Throughout this academic year, we have learned about European policy making, immigration issues in the United States, OECD´s effort to put up with the current crisis, Spain’s unemployment and labor market and why Northern countries engage in intra-industry trade. My contribution to this blog is oriented towards the Southern Cone of the globe, and is a personal assessment of some of the challenges that Latin America in particular, faces as a region today.

Cover for the book “Enough of Histories” of Andrés Oppenheimer by artist Alfredo Sabat (2010)

While many countries in the north confront one of the worst financial crisis in history, the ability that Latin American countries have had to adapt to the recent crisis has been remarkable. Nevertheless, what was first called as the Latin American boom now appears to be coming to an end.

How much of economic history stretching from hunter gather to modern day financial crisis can one really learn in five weeks? As it turns out, one can learn rather a lot. As anyone who braved Pro Voth’s course will tell you, economic growth as we know it is a very recent phenomenon. Up until before the Industrial Revolution, economic growth had remained stagnant for hundreds of years. This is a thought that should fester when considering that during the lifetime of the likes of Leonardo da Vinci, Galileo, Gutenberg etc. incomes and living standards remained essentially unchanged. As such, The Rise of the Global Economy set out to answer the questions: when did growth occur, why did it take so long, what finally caused it and what did we do with it.